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The ability to have the same experience for different user groups (i.e.,accessibility) is one of the most important characteristics of Web-basedsystems. The same is true for Knowledge Graph Question Answering (KGQA) systemsthat provide the access to Semantic Web data via natural language interface.While following our research agenda on the multilingual aspect of accessibilityof KGQA systems, we identified several ongoing challenges. One of them is thelack of multilingual KGQA benchmarks. In this work, we extend one of the mostpopular KGQA benchmarks - QALD-9 by introducing high-quality questions'translations to 8 languages provided by native speakers, and transferring theSPARQL queries of QALD-9 from DBpedia to Wikidata, s.t., the usability andrelevance of the dataset is strongly increased. Five of the languages -Armenian, Ukrainian, Lithuanian, Bashkir and Belarusian - to our best knowledgewere never considered in KGQA research community before. The latter two of thelanguages are considered as "endangered" by UNESCO. We call the extendeddataset QALD-9-plus and made it available onlinehttps://github.com/Perevalov/qald_9_plus.

QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakers